4 citations · 18 across the 13 of their papers we have counts for
6 papers · 1 filter
One-Shot Manipulation Strategy Learning by Making Contact Analogies
Yuyao Liu, Jiayuan Mao, Joshua Tenenbaum +2
We present a novel approach, MAGIC (manipulation analogies for generalizable intelligent contacts), for one-shot learning of manipulation strategies with fast and extensive general…
Few-Shot Task Learning through Inverse Generative Modeling
Aviv Netanyahu, Yilun Du, Antonia Bronars +4
Learning the intents of an agent, defined by its goals or motion style, is often extremely challenging from just a few examples. We refer to this problem as task concept learning a…
Potential Based Diffusion Motion Planning
Yunhao Luo, Chen Sun, Joshua B. Tenenbaum +1
Effective motion planning in high dimensional spaces is a long-standing open problem in robotics. One class of traditional motion planning algorithms corresponds to potential-based…
Compositional Image Decomposition with Diffusion Models
Jocelin Su, Nan Liu, Yanbo Wang +2
Given an image of a natural scene, we are able to quickly decompose it into a set of components such as objects, lighting, shadows, and foreground. We can then envision a scene whe…
Learning Iterative Reasoning through Energy Diffusion
Yilun Du, Jiayuan Mao, Joshua B. Tenenbaum
We introduce iterative reasoning through energy diffusion (IRED), a novel framework for learning to reason for a variety of tasks by formulating reasoning and decision-making probl…
HAZARD Challenge: Embodied Decision Making in Dynamically Changing Environments
Qinhong Zhou, Sunli Chen, Yisong Wang +6
Recent advances in high-fidelity virtual environments serve as one of the major driving forces for building intelligent embodied agents to perceive, reason and interact with the ph…